About: Assessing Ebola-related web search behaviour: insights and implications from an analytical study of Google Trends-based query volumes

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Assessing Ebola-related web search behaviour: insights and implications from an analytical study of Google Trends-based query volumes
Creator	Amicizia, Daniela Gasparini, Roberto Panatto, Donatella Alicino, Cristiano Faccio, Valeria Icardi, Giancarlo Orsi, Andrea Bragazzi, Nicola
topic	covid:47c38815f36cc14e7160f1890cda9f39b7e1d778#this
source	Medline; PMC
abstract	BACKGROUND: The 2014 Ebola epidemic in West Africa has attracted public interest worldwide, leading to millions of Ebola-related Internet searches being performed during the period of the epidemic. This study aimed to evaluate and interpret Google search queries for terms related to the Ebola outbreak both at the global level and in all countries where primary cases of Ebola occurred. The study also endeavoured to look at the correlation between the number of overall and weekly web searches and the number of overall and weekly new cases of Ebola. METHODS: Google Trends (GT) was used to explore Internet activity related to Ebola. The study period was from 29 December 2013 to 14 June 2015. Pearson’s correlation was performed to correlate Ebola-related relative search volumes (RSVs) with the number of weekly and overall Ebola cases. Multivariate regression was performed using Ebola-related RSV as a dependent variable, and the overall number of Ebola cases and the Human Development Index were used as predictor variables. RESULTS: The greatest RSV was registered in the three West African countries mainly affected by the Ebola epidemic. The queries varied in the different countries. Both quantitative and qualitative differences between the affected African countries and other Western countries with primary cases were noted, in relation to the different flux volumes and different time courses. In the affected African countries, web query search volumes were mostly concentrated in the capital areas. However, in Western countries, web queries were uniformly distributed over the national territory. In terms of the three countries mainly affected by the Ebola epidemic, the correlation between the number of new weekly cases of Ebola and the weekly GT index varied from weak to moderate. The correlation between the number of Ebola cases registered in all countries during the study period and the GT index was very high. CONCLUSION: Google Trends showed a coarse-grained nature, strongly correlating with global epidemiological data, but was weaker at country level, as it was prone to distortions induced by unbalanced media coverage and the digital divide. Global and local health agencies could usefully exploit GT data to identify disease-related information needs and plan proper communication strategies, particularly in the case of health-threatening events. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40249-015-0090-9) contains supplementary material, which is available to authorized users.
has issue date	2015-12-10(xsd:dateTime)
bibo:doi	10.1186/s40249-015-0090-9
bibo:pmid	26654247
has license	cc-by
sha1sum (hex)	47c38815f36cc14e7160f1890cda9f39b7e1d778
schema:url	https://doi.org/10.1186/s40249-015-0090-9
resource representing a document's title	Assessing Ebola-related web search behaviour: insights and implications from an analytical study of Google Trends-based query volumes
has PubMed Central identifier	PMC4674955
has PubMed identifier	26654247
schema:publication	Infect Dis Poverty
resource representing a document's body	covid:47c38815f36cc14e7160f1890cda9f39b7e1d778#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/47c38815f36cc14e7160f1890cda9f39b7e1d778
is schema:about of	named entity 'USED' named entity 'JUNE' named entity 'WORLDWIDE' named entity 'STRATEGIES' named entity 'WESTERN' named entity 'GREATEST' named entity 'NATURE' named entity 'INFORMATION' named entity 'INTERNET' named entity 'PRONE' named entity 'HEALTH AGENCIES' named entity 'INTEREST' named entity 'DATA' named entity 'LEVEL' named entity 'RESULTS' named entity 'PRIMARY' named entity 'EVALUATE' named entity 'RELATIVE' named entity 'PUBLIC' named entity 'PEARSON' named entity 'TO IDENTIFY' named entity 'MEDIA COVERAGE' named entity 'EXPLOIT' named entity 'STUDY' named entity 'UNBALANCED' named entity 'EPIDEMIC' named entity 'DIFFERENT' named entity 'TRENDS' named entity 'PERFORMED' named entity 'COUNTRIES' named entity '27S' named entity 'CONCENTRATED' named entity 'AFFECTED' named entity 'ACTIVITY' named entity 'DISEASE' named entity 'epidemiological' named entity 'June' named entity 'Western countries' named entity 'Results' named entity 'worldwide' named entity 'Human Development Index' named entity 'time' named entity 'number' named entity 'performed' named entity 'However' named entity 'FLUX' named entity 'INTERPRET' named entity 'DIGITAL DIVIDE' named entity 'NOTED' named entity 'MODERATE' named entity 'VOLUMES' named entity 'WEEKLY' named entity 'DEPENDENT VARIABLE' named entity 'RELATION' named entity 'BEING' named entity 'BUT' named entity 'WEAK' named entity 'NATIONAL' named entity 'DISTORTIONS' named entity 'VERY HIGH' named entity 'AREAS' named entity 'CAPITAL' named entity 'TIME' named entity 'USING' named entity 'QUALITATIVE' named entity 'PLAN' named entity 'INDEX' named entity 'CASE' named entity 'COARSE' named entity 'LEADING' named entity 'MULTIVARIATE REGRESSION' named entity 'DECEMBER'

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